Deep learning-based medical devices and differential diagnosis tools to save time while increasing confidence & improving reporting quality
Facing increasing workloads, radiologists must choose between longer working hours or decreased time spent evaluating images. This problem is compounded by the global radiologist shortage. Making matters even worse, new treatments require more complex diagnosis: about 20% of cases call for additional research from many sources, requiring up to 20 minutes each with a questionable rate of success. All these factors lead to delays, missed findings, inconsistent reporting quality and high overtime expenses. That’s why contextflow develops deep learning-based medical devices to help combat these challenges.
Our 3D image-based search engine (SEARCH) provides radiologists everything they need to solve difficult cases within seconds, reducing the time to search and overtime expense while improving reporting quality and confidence. It is currently being utilized to search for 19 different patterns in lung CTs, including those related to COVID-19. Additional organs, modalities and features are forthcoming. Results from our first clinical study in collaboration with the Medical University of Vienna (MUW) and Vienna General Hospital (AKH) are forthcoming in 2021.
Our prioritization tool (TRIAGE) automatically informs doctors which patients are known to have disease patterns present, thereby improving workflow efficiency even further by directing your attention to time-sensitive patients.
Most importantly, all our solutions integrate directly into your PACS/RIS. We currently have integrations with the following PACS: Agfa, Medigration, Philips, Sectra, Wellbeing. Don’t see what you’re looking for? Let us know! We’re more than happy to support your provider with new integrations.